Flow cytometric expression of CD71, CD81, CD44 and CD39 in B cell lymphoma.

Flow cytometry is a useful ancillary tool for the diagnosis of nodal B cell lymphomas. Well-established antigens have diagnostic limitations. This study aimed to assess the expression of CD71, CD81, CD44 and CD39 by flow cytometry in B cell lymphomas. Expression of these 4 antigens was queried in 185 samples with a diagnosis of a B cell lymphoma according to a histological examination of the lymph node and the World Health Organization (WHO) classification (follicular lymphoma [FL, n = 96], diffuse large B cell lymphoma/High grade B cell lymphoma [DLBCL/HGBH, n = 48], marginal zone lymphoma/lymphoplasmacytic lymphoma [MZL/LPL, n = 14], chronic lymphocytic leukemia/small lymphocytic lymphoma [CLL, n = 10], mantle cell lymphoma [MCL, n = 11], Burkitt lymphoma [BL, n = 4] and other [n = 2]). CD81 was bright and CD44 was dim in germinal center-derived malignancies, particularly aggressive lymphomas (BL and CD10-positive DLBCL/HGBL). CD81 was very dim in CLL. CD71 was bright in aggressive lymphomas (DLBCL/HGBL and BL). CD39 was bright in CD10-negative DLBCL. CD71 appeared valuable in the differential diagnosis between indolent and aggressive lymphomas, CD39 between CD10-negative DLBCL and MZL/LPL and CD81 between MCL and CLL. To conclude, we report the expression of CD71, CD81, CD44 and CD39 by FC in B cell lymphomas. Further studies will have to determine the value they add to specific FC panels.

Concordance between flow cytometry CLL scores.

INTRODUCTION: Multiple flow cytometry scores/diagnostic systems for the classification of leukemic lymphoproliferative disorders (LPD) have been published but few have been compared between them. PATIENTS AND METHODS: We classified a cohort of leukemic LPD based on eleven published flow cytometry scores/diagnostic systems and compared their classification as chronic lymphocytic leukemia (CLL) or non-CLL LPD. RESULTS: 329 patients were included. Patients classified as CLL ranged from 46% to 73%, depending on the score/diagnostic system used. All eleven scores/diagnostic systems agreed in 184/324 (57%) of patients while in 58/324 (18%) at least two scores/diagnostic systems classified the patient differently (from the majority). Fleiss kappa was 0.74, but pairwise agreement was variable (Cohen's kappa: 0.48 to 0.87). CONCLUSION: This study found a suboptimal agreement between published flow cytometry scores/diagnostic systems for the classification of LPD.

Divergent leukaemia subclones as cellular models for testing vulnerabilities associated with gains in chromosomes 7, 8 or 18.

Haematopoietic malignancies are frequently characterized by karyotypic abnormalities. The development of targeted drugs has been pioneered with compounds against gene products of fusion genes caused by chromosomal translocations. While polysomies are equally frequent as translocations, for many of them we are lacking therapeutic approaches aimed at synthetic lethality. Here, we report two new cell lines, named MBU-7 and MBU-8, that differ in complete trisomy of chromosome18, a partial trisomy of chromosome 7 and a tetrasomy of the p-arm of chromosome 8, but otherwise share the same mutational pattern and complex karyotype. Both cell lines are divergent clones of U-937 cells and have the morphology and immunoprofile of monocytic cells. The distinct karyotypic differences between MBU-7 and MBU-8 are associated with a difference in the specific response to nucleoside analogues. Taken together, we propose the MBU-7 and MBU-8 cell lines described here as suitable in vitro models for screening and testing vulnerabilities that are associated with the disease-relevant polysomies of chromosome 7, 8 and 18.

Diagnostic performance of the ClearLLab 10C B cell tube.

INTRODUCTION: Pre-analytical and analytical errors can threaten the reliability of flow cytometry (FC) results. A potential solution to some of these is the use of dry, pre-mixed antibodies, such as the ClearLLab 10C system. The purpose of the present study was to compare the diagnostic performance of the ClearLLab 10C B cell tube with that of our standard laboratory practice. METHODS: We compared the diagnoses made with the ClearLLab 10C B cell tube (experimental strategy) with those made with standard laboratory practice (standard strategy). Samples were selected aiming for representation of the full spectrum of B cell disorders, with an emphasis on mature B cell malignancies, as well as healthy controls. RESULTS: We included 116 samples (34 normal controls, 4 acute lymphoblastic leukemias, 54 mature lymphoproliferative disorders in peripheral blood and bone marrow, 3 myelomas, 6 bone marrow samples with involvement by lymphoma and 1 with elevated hematogone count, 14 lymph node samples, 1 cerebrospinal fluid, and 1 pleural effusion). There were two diagnostic errors (1.7%). The agreement between the two strategies in the percentage of CD19 cells and fluorescence intensity of CD5, CD19, CD20, CD200, and CD10 was very good. CONCLUSIONS: In this study, the ClearLLab 10C B cell tube performed similarly to our standard laboratory practice to diagnose and classify mature B cell malignancies.

Flow Cytometry in the Differential Diagnosis of CD10-Positive Nodal Lymphomas.

BACKGROUND: Differences between follicular lymphoma (FL) and diffuse large B-cell lymphoma/high-grade B-cell lymphoma (DLBCL/HGBL) by flow cytometry are underexplored. METHODS: We retrospectively assessed flow cytometry results from 191 consecutive lymph node biopsies diagnosed with FL or DLBCL/HGBL. RESULTS: The only parameters that differed between the 2 groups in the derivation cohort were forward scatter and side scatter (P < 10-6; area under the curve [AUC], 0.75-0.8) and %CD23 (P = .004; area under the receiver characteristic operating curve, 0.64). However, since light scatter characteristics did not distinguish between grade 3 FL and DLBCL/HGBL, we set out to develop a model with high sensitivity for the exclusion of the latter. Several models, including FS and %CD23, were tested, and 2 models showed a sensitivity of >0.90, with negative predictive values of ≥0.95, albeit with low specificity (0.45 to 0.57). CONCLUSION: Two simple models enable the exclusion of DLBCL/HGBL with a high degree of confidence.

FMOD expression in whole blood aids in distinguishing between chronic lymphocytic leukemia and other leukemic lymphoproliferative disorders. A pilot study.

BACKGROUND: Within the hematopoietic compartment, fibromodulin (FMOD) is almost exclusively expressed in chronic lymphocytic leukemia (CLL) lymphocytes. We set out to determine whether FMOD could be of help in diagnosing borderline lymphoproliferative disorders (LPD). METHODS: We established 3 flow cytometry-defined groups (CLL [n = 65], borderline LPD [n = 28], broadly defined as those with CLLflow score between 35 and -20 or discordant CD43 and CLLflow, and non-CLL LPD [n = 40]). FMOD expression levels were determined by standard RT-PCR in whole-blood samples. Patients were included regardless of lymphocyte count but with tumor burden ≥40%. RESULTS: FMOD expression levels distinguished between CLL (median 98.5, interquartile range [IQR] 37.8-195.1) and non-CLL LPD (median 0.012, IQR 0.003-0.033) with a sensitivity and specificity of 1. Most borderline LPDs were CD5/CD23/CD200-positive with no loss of B-cell antigens and negative or partial expression of CD43. 16/22 patients with available cytogenetic analysis showed trisomy 12. In 25/28 (89%) of these patients, FMOD expression levels fell between CLL and non-CLL (median 3.58, IQR 1.06-6.21). DISCUSSION: This study could suggest that borderline LPDs may constitute a distinct group laying in the biological spectrum of chronic leukemic LPDs. Future studies will have to confirm these results with other biological data. Quantification of FMOD can potentially be of help in the diagnosis of phenotypically complex LPDs.

Refining the Limits of Borderline Lymphoproliferative Disorders.

BACKGROUND: The concept of borderline lymphoproliferative disorder (LPD) has not been clearly defined. METHODS: This study aimed to classify patients with leukemic LPD (n = 597, excluding hairy cell leukemia, mantle cell lymphomas, and CD10-positive LPDs) into CLL or non-CLL applying three diagnostic strategies (the D'Arena and CLLflow scores and CD43 expression) and to better characterize unclassified patients. RESULTS: Patients with concurring CLL-like (n = 441) or non-CLL like (n = 99) results with the three diagnostic strategies were determined to have CLL and non-CLL, respectively. Patients with discordant results (n = 57) were analyzed taking into consideration each individual cytometric marker and cytogenetic data: 41 were classified (11 CLL, 30 non-CLL) and 16 (2.7% of the entire series) could not and were considered borderline LPD. Excluding borderline LPD, the CLLflow score had the highest accuracy of the three strategies. With the addition of CD43 no patient was misclassified. With the aid of hierarchical clustering, 12 of the 16 borderline patients seemed to fall into two well-defined antigenic groups. None of the diagnostic strategies could reliably pick out borderline LPD. CONCLUSION: The combination of the CLLflow score and CD43 generally has a high diagnostic accuracy for leukemic LPD but it is not reliable to identify or diagnose borderline LPD. This latter group needs further study to determine its underlying biology. © 2018 International Clinical Cytometry Society.